The Internet of Things (IoT) is one of the most intriguing technological revolutions of the last few years due to its rapid expansion. The advancement of IoT applications is dependent on standard and real-time communi...
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Recent research on graph embedding has achieved success in various applications. Most graph embedding methods preserve the proximity in a graph into a manifold in an embedding space. We argue an important but neglecte...
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The problem of efficient and high-quality clustering of extreme scale datasets with complex clustering structures continues to be one of the most challenging data analysis problems. An innovate use of data cloud would...
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This paper presents STGTP, which combines graph and text-based techniques for stance detection of social media posts. This model learns from the text in the post and the relationships between the posts due to users co...
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In order to perform any operation in an RDF graph, it is recommendable to know the expected topology of the targeted information. Some technologies have been developed in the last years to describe the expected shapes...
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We study Monte Carlo tree search (MCTS) in zero-sum extensive-form games with perfect information and simultaneous moves. We present a general template of MCTS algorithms for these games, which can be instantiated by ...
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We study Monte Carlo tree search (MCTS) in zero-sum extensive-form games with perfect information and simultaneous moves. We present a general template of MCTS algorithms for these games, which can be instantiated by various selection methods. We formally prove that if a selection method is Ε-Hannan consistent in a matrix game and satisfies additional requirements on exploration, then the MCTS algorithm eventually converges to an approximate Nash equilibrium (NE) of the extensive-form game. We empirically evaluate this claim using regret matching and Exp3 as the selection methods on randomly generated games and empirically selected worst case games. We confirm the formal result and show that additional MCTS variants also converge to approximate NE on the evaluated games.
The classical algorithm of finding association rules generated by a frequent itemset has to generate all nonempty subsets of the frequent itemset as candidate set of consequents. Xiongfei Li aimed at this and proposed...
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The classical algorithm of finding association rules generated by a frequent itemset has to generate all nonempty subsets of the frequent itemset as candidate set of consequents. Xiongfei Li aimed at this and proposed an improved algorithm. The algorithm finds all consequents layer by layer, so it is breadth-first. In this paper, we propose a new algorithm Generate Rules by using Set-Enumeration Tree (GRSET) which uses the structure of Set-Enumeration Tree and depth-first method to find all consequents of the association rules one by one and get all association rules correspond to the consequents. Experiments show GRSET algorithm to be practicable and efficient.
Trustworthy service composition is an extremely important task when service composition becomes infeasible or even fails in an environment which is open,autonomic,uncertain and *** paper presents a trustworthy service...
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Trustworthy service composition is an extremely important task when service composition becomes infeasible or even fails in an environment which is open,autonomic,uncertain and *** paper presents a trustworthy service composition method based on an improved Cross generation elitist selection,Heterogeneous recombination,Catacly-smic mutation(CHC) Trustworthy Service Composition Method(CHC-TSCM) genetic *** firstly obtains the total trust degree of the individual service using a trust degree measurement and evaluation model proposed in previous *** combination and computation then are performed according to the structural relation of the composite ***,the optimal trustworthy service composition is acquired by the improved CHC genetic *** results show that CHC-TSCM can effectively solve the trustworthy service composition *** with GODSS and TOCSS,this new method has several advantages:1) a higher service composition successrate;2) a smaller decline trend of the service composition success-rate,and 3) enhanced stability.
It is an important strategy to investigate customer’s sensibility and preference in the merchandise environment changing to the user oriented. We propose the design recommender system, which exposes its collection in...
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Feature selection is an effective technique to put the high dimension of data down, which is prevailing in many application domains, such as text categorization and bio-informatics, and can bring many advantages, such...
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